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William D. Riihiluoma; Zeynep Topdemir; John R. Thompson – Physical Review Physics Education Research, 2025
The ability to relate physical concepts and phenomena to multiple mathematical representations--and to move fluidly between these representations--is a critical outcome expected of physics instruction. In upper-division quantum mechanics, students must work with multiple symbolic notations, including some that they have not previously encountered.…
Descriptors: Undergraduate Students, College Faculty, Physics, Science Instruction
Umut Atasever; Francis L. Huang; Leslie Rutkowski – Large-scale Assessments in Education, 2025
When analyzing large-scale assessments (LSAs) that use complex sampling designs, it is important to account for probability sampling using weights. However, the use of these weights in multilevel models has been widely debated, particularly regarding their application at different levels of the model. Yet, no consensus has been reached on the best…
Descriptors: Mathematics Tests, International Assessment, Elementary Secondary Education, Foreign Countries
Liqun Yin; Ummugul Bezirhan; Matthias von Davier – International Electronic Journal of Elementary Education, 2025
This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…
Descriptors: Multivariate Analysis, Cutting Scores, Achievement Tests, Foreign Countries
Lyu, Weicong; Kim, Jee-Seon; Suk, Youmi – Journal of Educational and Behavioral Statistics, 2023
This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…
Descriptors: Hierarchical Linear Modeling, Bayesian Statistics, Causal Models, Statistical Inference
Hong, Jeehye; Kim, Hyunjung; Hong, Hun-Gi – Asia-Pacific Science Education, 2022
This study explored science-related variables that have an impact on the prediction of science achievement groups by applying the educational data mining (EDM) method of the random forest analysis to extract factors associated with students categorized in three different achievement groups (high, moderate, and low) in the Korean data from the 2015…
Descriptors: Science Achievement, Prediction, Teaching Methods, Science Teachers
Young, Nicholas T.; Caballero, Marcos D. – Physical Review Physics Education Research, 2021
One argument for keeping the physics Graduate Record Exam (GRE) is that it can help applicants who might otherwise be missed in the admissions process stand out. In this work, we evaluate whether this claim is supported by physics graduate school admissions decisions. We used admissions data from five Ph.D.-granting physics departments over a…
Descriptors: College Entrance Examinations, Graduate Study, College Applicants, Selective Admission
Westrick, Paul A.; Marini, Jessica P.; Shmueli, Doron; Young, Linda; Shaw, Emily J.; Ng, Helen – College Board, 2020
In May 2019, College Board published the first national operational SAT® validity study on the new SAT introduced in 2016. Based on data from more than 221,000 students across 169 four-year colleges and universities, the study showed that the SAT was essentially as effective as high school grades in predicting students' college performance and…
Descriptors: College Entrance Examinations, Test Validity, Prediction, Grades (Scholastic)
Stamovlasis, Dimitrios – Complicity: An International Journal of Complexity and Education, 2017
This paper discusses investigations in science education addressing the nonlinear dynamical hypothesis. Learning science is a suitable field for applying interdisciplinary research and predominately for testing psychological theories. It was demonstrated that in this area the paradigm of complexity and nonlinear dynamics have offered theoretical…
Descriptors: Science Education, Educational Research, Research Methodology, Predictor Variables
Adkins, Michael; Noyes, Andrew – International Journal of Science and Mathematics Education, 2018
The mathematical preparedness of science undergraduates has been a subject of debate for some time. This paper investigates the relationship between school mathematics attainment and degree outcomes in biology and chemistry across England, a much larger scale of analysis than has hitherto been reported in the literature. A unique dataset which…
Descriptors: Foreign Countries, Mathematics Achievement, Biology, Chemistry
Harrison, David J.; Saito, Laurel; Markee, Nancy; Herzog, Serge – European Journal of Engineering Education, 2017
To examine the impact of a hybrid-flipped model utilising active learning techniques, the researchers inverted one section of an undergraduate fluid mechanics course, reduced seat time, and engaged in active learning sessions in the classroom. We compared this model to the traditional section on four performance measures. We employed a propensity…
Descriptors: Mechanics (Physics), Science Instruction, Blended Learning, Instructional Effectiveness
Phelan, Julia; Egger, Jeffrey; Kim, Junok; Choi, Kilchan; Keum, Eunhee; Chung, Gregory K. W. K.; Baker, Eva L. – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2021
The National Math + Science Initiative (NMSI) is a nonprofit organization committed to improving educational outcomes that traces its roots back to the early 1990s. NMSI's College Readiness Program (CRP) is a long-standing program with the goal of promoting STEM education in high schools to improve students' preparation for college. The three-year…
Descriptors: College Readiness, Nonprofit Organizations, Program Evaluation, STEM Education
Northwest Evaluation Association, 2016
This guide was created as a resource to help families better understand "Measures of Academic Progress"® (MAP®), and their child's results. The guide provides answers to a variety of questions such as: "What is MAP?"; "What does MAP measure?"; "How do schools and teachers use MAP scores?"; "Can MAP tell…
Descriptors: Scores, Academic Achievement, Achievement Tests, Reading Achievement
Al Tamimi, Abdul Rehman – Journal of Education and Learning, 2018
This study tried to explore the degree of representation of math textbooks for grades (4-8) in the Kingdom of Saudi Arabia concerning the key concepts, shape, and levels of questions used in the TIMSS test. The study population of this study includes both students and teachers from fourth grade to eighth grade. The goal of this study was…
Descriptors: Mathematics Instruction, Textbooks, Content Analysis, Instructional Effectiveness
Stapleton, Laura M.; Kang, Yoonjeong – Sociological Methods & Research, 2018
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…
Descriptors: Probability, Hierarchical Linear Modeling, Sampling, Inferences
Greenberg Motamedi, Jason; Serrano, Diana; Hanson, Havala – Education Northwest, 2020
Education Northwest partnered with Oregon Mathematics, Engineering & Science Achievement (MESA) to measure the effect of program participation by comparing academic outcomes of two groups of students: those who participated in MESA and a matched group of peers who did not. All things that we could measure and are linked to student academic…
Descriptors: High School Graduates, Graduation, Program Effectiveness, Middle School Students
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